{"title":"高分一号宽视场传感器的初步比较","authors":"Feng Chen, Wenhao Zhang, Jing Hu, Baisong Zhao, Chenxing Wang, Yuejun Song","doi":"10.1109/Geoinformatics57846.2022.9963821","DOIUrl":null,"url":null,"abstract":"The wide field of view (WFV) sensor as one of the imaging systems onboard Gaofen-l (GF-1) satellite acquires multispectral imagery with a spatial resolution of 16 m. The medium spatial resolution as well as high temporal resolution and wide swath makes the GF-1 WFV multispectral imagery more suitable for monitoring over large-scale surface. Currently, investigations mainly focusing on processing and application of the GF-1 WFV data have been widely reported. There are four GF-1 WFV sensors (namely including WFV1, WFV2, WFV3, and WFV4) designed with similar characterization, but having discrepancies among them. However, comparability among the four WFV sensors has not been discussed fully. In this paper, preliminary findings on comparison of the GF-1 WFV sensors are presented. Relatively significant discrepancies among the GF-1 WFV sensors are observed in spectral response function and the derived indicators (i.e. channel effective wavelength and the percentage of overlap) for the red and green channels, whereas the differences are less obvious for the blue channel. The between-sensor differences generally vary with the channel, which are also associated with the sensors in comparison. Overall, the WFV1 and the WFV2 show comparability in all channels (i.e. the blue, green, red, and near-infrared channels). Furthermore, the findings based on a collection of synthesized GF-1 WFV data suggest that a general linear model may not be sufficient to improve between-sensor comparability for all individual land use/cover classes, although it is effective to reduce the overall between-sensor difference. Potential uncertainty in channel reflectance introduced through transformation model should be taken into account for the applications followed by.","PeriodicalId":281958,"journal":{"name":"2022 29th International Conference on Geoinformatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Preliminary comparisons among the Gaofen-1 wide field of view sensors\",\"authors\":\"Feng Chen, Wenhao Zhang, Jing Hu, Baisong Zhao, Chenxing Wang, Yuejun Song\",\"doi\":\"10.1109/Geoinformatics57846.2022.9963821\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The wide field of view (WFV) sensor as one of the imaging systems onboard Gaofen-l (GF-1) satellite acquires multispectral imagery with a spatial resolution of 16 m. The medium spatial resolution as well as high temporal resolution and wide swath makes the GF-1 WFV multispectral imagery more suitable for monitoring over large-scale surface. Currently, investigations mainly focusing on processing and application of the GF-1 WFV data have been widely reported. There are four GF-1 WFV sensors (namely including WFV1, WFV2, WFV3, and WFV4) designed with similar characterization, but having discrepancies among them. However, comparability among the four WFV sensors has not been discussed fully. In this paper, preliminary findings on comparison of the GF-1 WFV sensors are presented. Relatively significant discrepancies among the GF-1 WFV sensors are observed in spectral response function and the derived indicators (i.e. channel effective wavelength and the percentage of overlap) for the red and green channels, whereas the differences are less obvious for the blue channel. The between-sensor differences generally vary with the channel, which are also associated with the sensors in comparison. Overall, the WFV1 and the WFV2 show comparability in all channels (i.e. the blue, green, red, and near-infrared channels). Furthermore, the findings based on a collection of synthesized GF-1 WFV data suggest that a general linear model may not be sufficient to improve between-sensor comparability for all individual land use/cover classes, although it is effective to reduce the overall between-sensor difference. Potential uncertainty in channel reflectance introduced through transformation model should be taken into account for the applications followed by.\",\"PeriodicalId\":281958,\"journal\":{\"name\":\"2022 29th International Conference on Geoinformatics\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 29th International Conference on Geoinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/Geoinformatics57846.2022.9963821\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 29th International Conference on Geoinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Geoinformatics57846.2022.9963821","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Preliminary comparisons among the Gaofen-1 wide field of view sensors
The wide field of view (WFV) sensor as one of the imaging systems onboard Gaofen-l (GF-1) satellite acquires multispectral imagery with a spatial resolution of 16 m. The medium spatial resolution as well as high temporal resolution and wide swath makes the GF-1 WFV multispectral imagery more suitable for monitoring over large-scale surface. Currently, investigations mainly focusing on processing and application of the GF-1 WFV data have been widely reported. There are four GF-1 WFV sensors (namely including WFV1, WFV2, WFV3, and WFV4) designed with similar characterization, but having discrepancies among them. However, comparability among the four WFV sensors has not been discussed fully. In this paper, preliminary findings on comparison of the GF-1 WFV sensors are presented. Relatively significant discrepancies among the GF-1 WFV sensors are observed in spectral response function and the derived indicators (i.e. channel effective wavelength and the percentage of overlap) for the red and green channels, whereas the differences are less obvious for the blue channel. The between-sensor differences generally vary with the channel, which are also associated with the sensors in comparison. Overall, the WFV1 and the WFV2 show comparability in all channels (i.e. the blue, green, red, and near-infrared channels). Furthermore, the findings based on a collection of synthesized GF-1 WFV data suggest that a general linear model may not be sufficient to improve between-sensor comparability for all individual land use/cover classes, although it is effective to reduce the overall between-sensor difference. Potential uncertainty in channel reflectance introduced through transformation model should be taken into account for the applications followed by.